Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for plant stand management, comprising: capturing, by at least one sensor unit, images of a plant stand; receiving, by a controller, said captured images; processing, by said controller, said captured images for determining one or more characteristics of said plant stand; generating, by said controller, one or more control signals based on said one or more characteristics; sending, by said controller, said one or more control signals to at least one applicator; performing, by said at least one applicator, at least one action on said plant stand based on said one or more control signals; storing, in a memory of said controller, image processing software, and a location of said at least one sensor unit and a location of said at least one applicator relative to a GPS device; and executing, by a processor of said controller, said image processing software for processing said captured images, GPS signals from said GPS device, and said location of said at least one sensor unit mounted to an agricultural vehicle relative to said GPS device for determining said one or more characteristics of said plant stand, wherein said one or more characteristics of said plant stand is a global location of one or more plants in said plant stand.
This invention relates to automated plant stand management in agriculture, addressing the challenge of efficiently monitoring and treating plant stands to optimize crop yield and resource use. The system uses at least one sensor unit mounted on an agricultural vehicle to capture images of a plant stand. A controller receives these images and processes them to determine key characteristics of the plant stand, such as the global location of individual plants within the stand. The controller generates control signals based on these characteristics and sends them to at least one applicator, which then performs actions like applying fertilizers, pesticides, or other treatments to the plant stand. The controller includes image processing software and stores the locations of the sensor unit and applicator relative to a GPS device. The processor executes the software to analyze the captured images, GPS signals, and the relative positions of the sensor and applicator to accurately determine plant locations. This automated approach enables precise, location-specific interventions, improving efficiency and reducing waste in agricultural operations.
2. The method according to claim 1 , wherein said one or more plants are associated with one or more rows, and wherein said one or more characteristics of said plant stand comprises at least one of a morphology value of said one or more plants, distances between said one or more plants, distances between said one or more plants and one or more features of said plant stand, a global location of said one or more plants, and missing plants.
This invention relates to agricultural monitoring and analysis, specifically for assessing plant stands in a field. The technology addresses the challenge of efficiently capturing and analyzing key characteristics of plant stands to optimize crop management. The method involves monitoring one or more plants associated with one or more rows in a field. The system evaluates various characteristics of the plant stand, including morphology values of the plants, distances between individual plants, distances between plants and other features within the plant stand, the global location of the plants, and the presence of missing plants. These characteristics are used to generate insights into plant health, spacing, and distribution, enabling better decision-making for planting, irrigation, and harvesting. The method leverages these measurements to improve agricultural productivity by identifying areas requiring intervention, such as replanting or targeted treatment. The system may integrate with existing agricultural equipment or sensors to collect and process the data in real-time or batch mode. The solution enhances precision agriculture by providing detailed, actionable data on plant stand conditions.
3. The method according to claim 2 , wherein said at least one applicator comprises at least one nozzle coupled to at least one direction means and at least one fluid switch, said at least one fluid switch coupled to a storage unit containing an agent via at least one pump, and wherein said method further comprises: receiving, by said at least one direction means, one or more positioning control signals; receiving, by said at least one fluid switch, one or more switching control signals; and directing a dose of said agent to said global location of a plant in said plant stand if at least one of said morphology value of said plant is below a threshold morphology value, a distance between said plant and another plant of said plant stand is below a plant separation threshold value, and a shortest distance between said plant and a nearest row is greater than a row offset value.
This invention relates to automated plant treatment systems, specifically methods for precisely applying agents to plants based on morphological and positional data. The system addresses the challenge of optimizing plant growth by selectively treating plants that meet specific conditions, such as insufficient growth, improper spacing, or incorrect row positioning. The method uses an applicator with at least one nozzle, a direction mechanism, and a fluid switch connected to a storage unit containing an agent via a pump. The direction mechanism receives positioning control signals to aim the nozzle, while the fluid switch receives switching control signals to release the agent. The system evaluates plant morphology, inter-plant spacing, and row alignment. If a plant's morphology value falls below a predefined threshold, the distance to neighboring plants is too close, and the plant is sufficiently offset from the nearest row, the system directs a dose of the agent to that plant. This targeted approach ensures efficient resource use and improves plant growth uniformity. The invention enhances agricultural automation by integrating real-time data analysis with precise agent delivery.
4. The method according to claim 3 , wherein said morphology value is based upon at least one of stem size of said plant, height of said plant, number of leaves of said plant, and dimensions of one or more of said leaves.
This invention relates to plant monitoring and analysis, specifically determining the morphology of plants to assess their health or growth characteristics. The method involves calculating a morphology value for a plant based on measurable physical attributes, including stem size, plant height, number of leaves, and dimensions of individual leaves. These parameters are used to derive a quantitative representation of the plant's structure, which can be applied in agricultural monitoring, automated harvesting, or precision farming. The morphology value may be derived from sensor data, such as images or measurements, and can be used to compare plants against growth models or detect abnormalities. By analyzing these morphological features, the system enables real-time or periodic assessment of plant development, allowing for targeted interventions like irrigation, nutrient adjustment, or pest control. The approach improves efficiency in plant cultivation by providing objective, data-driven insights into plant health and growth patterns.
5. The method according to claim 1 , wherein said one or more characteristics of said plant stand also includes at least one of a morphology value of said one or more plants, distances between said one or more plants, distances between said one or more plants and one or more features of said plant stand, and a global location of missing plants.
This invention relates to agricultural monitoring and analysis, specifically improving the assessment of plant stands in agricultural fields. The technology addresses the challenge of accurately evaluating plant growth and distribution to optimize crop management. The method involves analyzing one or more characteristics of a plant stand, including morphological features of individual plants, spatial relationships between plants, and the presence of missing plants. Morphology values describe physical attributes such as plant height, leaf density, or stem thickness. The method also measures distances between plants and between plants and other features within the plant stand, such as irrigation lines or soil markers. Additionally, it identifies the global location of missing plants, providing a comprehensive spatial map of plant distribution. This data helps farmers and agronomists detect issues like uneven growth, gaps in planting, or disease outbreaks, enabling targeted interventions. The system enhances precision agriculture by integrating detailed plant metrics with spatial analysis, improving yield predictions and resource allocation. The technology supports automated monitoring through sensors or imaging systems, reducing manual labor and increasing accuracy in field assessments.
6. The method according to claim 5 , wherein said at least one sensor unit is at least one camera, and wherein processing said captured images for determining said one or more characteristics of said plant stand is based on at least one of a distance between said at least one camera and a surface of said plant stand, a field of view of said at least one camera, and a distance between adjacent rows of said plant stand.
This invention relates to agricultural monitoring systems that use camera-based sensors to analyze plant stands. The technology addresses the challenge of accurately assessing plant growth and health by capturing and processing images to determine key characteristics of plant stands, such as plant density, spacing, and uniformity. The system employs at least one camera to capture images of the plant stand, and the captured images are processed to derive these characteristics based on factors including the distance between the camera and the plant surface, the camera's field of view, and the spacing between adjacent rows of plants. By analyzing these parameters, the system provides precise data for agricultural decision-making, such as optimizing planting density, detecting growth anomalies, and improving crop yield. The method ensures accurate measurements by accounting for variations in camera positioning and environmental conditions, enhancing the reliability of plant stand assessments in different agricultural settings.
7. The method according to claim 5 , comprising executing, by said processor, said image processing software for processing said captured images for generating augmented reality (AR) images, said AR images differentially augmented based on one or more of said morphology value of said one or more plants, said distances between said one or more plants, said distances between said one or more plants and one or more features of said plant stand, and said missing plants.
This invention relates to augmented reality (AR) systems for plant monitoring and analysis. The technology addresses the challenge of visually representing plant growth data in a way that enhances user understanding of plant health, spacing, and stand features. The method involves capturing images of a plant stand using a camera and analyzing the images to determine morphological characteristics of individual plants, distances between plants, distances between plants and stand features, and identifying missing plants. The system then processes these captured images using image processing software to generate AR images. The AR images are differentially augmented based on the morphology of the plants, plant-to-plant distances, plant-to-feature distances, and missing plant locations. This differential augmentation allows users to visually assess plant health, spacing irregularities, and stand features in an enhanced AR display. The system may also include a user interface for selecting specific plants or regions of the plant stand for detailed analysis. The AR visualization helps users quickly identify areas requiring attention, such as overcrowded or underperforming plants, and optimize planting strategies. The method improves upon traditional monitoring techniques by providing real-time, spatially accurate AR overlays that integrate multiple plant metrics into a single visual representation.
8. The method according to claim 7 , comprising modifying, by said processor, said AR images based upon modification of said plant stand, said modification of said plant stand based upon said at least one applicator performing said at least one action on said plant stand, generating, by said processor, first statistics from said AR images and second statistics from said modified AR images, and storing, by said processor, said first and second statistics in said memory.
This invention relates to augmented reality (AR) systems for monitoring and analyzing plant stands, particularly in agricultural applications. The technology addresses the challenge of dynamically tracking and evaluating plant growth and treatment effects in real-time using AR visualization and data analytics. The system uses AR to overlay digital representations of plant stands onto real-world images captured by a camera. A processor generates AR images that visually depict the plant stand, including its current state and any modifications. At least one applicator performs actions on the plant stand, such as applying treatments or adjusting growth conditions. The processor then modifies the AR images based on these actions, reflecting changes in the plant stand. For example, if a fertilizer is applied, the AR images may update to show expected growth patterns or health improvements. The system generates two sets of statistics: first statistics from the original AR images and second statistics from the modified AR images. These statistics may include metrics like plant density, growth rates, or treatment effectiveness. The processor stores both sets of statistics in memory for comparison and analysis, enabling users to assess the impact of applied actions on the plant stand over time. This approach provides a data-driven method for optimizing agricultural practices by visualizing and quantifying changes in plant stands.
9. The method according to claim 7 , further comprising displaying, on a display, said AR images.
A system and method for augmented reality (AR) visualization enhances user interaction with digital content overlaid on a physical environment. The technology addresses the challenge of seamlessly integrating virtual elements into real-world scenes while ensuring accurate alignment and user engagement. The method involves capturing real-time images of the physical environment using a camera, processing these images to identify and track specific features or markers, and generating augmented reality (AR) images based on the tracked features. These AR images are then displayed on a display device, such as a smartphone, tablet, or AR headset, in alignment with the physical environment. The system may also incorporate user input, such as gestures or voice commands, to interact with the AR content. The method ensures that the AR images remain stable and properly aligned with the physical environment, even as the user moves or the environment changes. This technology is applicable in fields such as gaming, education, navigation, and industrial training, where immersive and interactive AR experiences are beneficial.
10. The method according to claim 1 , wherein each image of said captured images comprises a plurality of pixels, said method further comprising: determining, by said controller, RGB intensity values of each pixel of said plurality of pixels; determining, by said controller, if said each pixel is a plant pixel based on said RGB intensity values; and processing, by said controller, only said determined plant pixels of said each image for determining said one or more characteristics of said plant stand.
This invention relates to image processing for agricultural applications, specifically analyzing plant stands to determine characteristics such as health, density, or growth patterns. The problem addressed is the need for efficient and accurate analysis of plant images to extract meaningful data while minimizing computational overhead by focusing only on relevant plant pixels. The method involves capturing multiple images of a plant stand using an imaging device. Each image is composed of pixels, and the system processes these pixels to identify and analyze only those belonging to plants. The controller first determines the RGB intensity values for each pixel in the captured images. Using these values, the controller classifies each pixel as either a plant pixel or a non-plant pixel. Only the identified plant pixels are then processed further to determine one or more characteristics of the plant stand, such as growth rate, health, or density. This selective processing reduces computational load and improves accuracy by excluding irrelevant background or non-plant elements from the analysis. The method ensures efficient and precise plant stand evaluation for agricultural monitoring and decision-making.
Unknown
June 9, 2020
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